OBJECTIVE: The purpose of our study was to compare the diagnostic performance of coronary CT angiography (CTA) subjected to model-based iterative reconstruction (IR) or hybrid IR to rule out coronary in-stent restenosis. METHODS: We enrolled 16 patients who harboured 22 coronary stents. They underwent coronary CTA on a 320-slice CT scanner. The images were reconstructed with hybrid IR (AIDR 3D) and model-based IR (FIRST) algorithms. We calculated the stent lumen attenuation increase ratio and measured the visible stent lumen diameter. Two blinded observers visually graded the likelihood of in-stent restenosis (lesions ≥ 50%) on hybrid IR and FIRST images. RESULTS: The stent lumen attenuation increase ratio on FIRST- was lower than on AIDR 3D images (0.20 vs 0.32). The ratio of the visible- compared to the true stent lumen diameter was higher on FIRST- than AIDR 3D images (52.5 vs 47.5%). Invasive coronary angiography identified five stents (22.7%) with significant in-stent restenosis. The use of FIRST improved the sensitivity (60 vs 100%), positive (75.0 vs 83.3%) and negative predictive value (88.9 vs 100%) and the accuracy (86.4 vs 95.5%) for the detection of in-stent restenosis. Specificity was 94.1% for both reconstruction methods. CONCLUSION: The model-based IR algorithm may improve diagnostic performance for the detection of in-stent restenosis. Advances in knowledge: Compared to hybrid IR, the new model-based IR algorithm reduced blooming artefacts and improved the image quality. It can be expected to improve diagnostic performance for the detection of in-stent restenosis on coronary CTA images.
OBJECTIVE: The purpose of our study was to compare the diagnostic performance of coronary CT angiography (CTA) subjected to model-based iterative reconstruction (IR) or hybrid IR to rule out coronary in-stent restenosis. METHODS: We enrolled 16 patients who harboured 22 coronary stents. They underwent coronary CTA on a 320-slice CT scanner. The images were reconstructed with hybrid IR (AIDR 3D) and model-based IR (FIRST) algorithms. We calculated the stent lumen attenuation increase ratio and measured the visible stent lumen diameter. Two blinded observers visually graded the likelihood of in-stent restenosis (lesions ≥ 50%) on hybrid IR and FIRST images. RESULTS: The stent lumen attenuation increase ratio on FIRST- was lower than on AIDR 3D images (0.20 vs 0.32). The ratio of the visible- compared to the true stent lumen diameter was higher on FIRST- than AIDR 3D images (52.5 vs 47.5%). Invasive coronary angiography identified five stents (22.7%) with significant in-stent restenosis. The use of FIRST improved the sensitivity (60 vs 100%), positive (75.0 vs 83.3%) and negative predictive value (88.9 vs 100%) and the accuracy (86.4 vs 95.5%) for the detection of in-stent restenosis. Specificity was 94.1% for both reconstruction methods. CONCLUSION: The model-based IR algorithm may improve diagnostic performance for the detection of in-stent restenosis. Advances in knowledge: Compared to hybrid IR, the new model-based IR algorithm reduced blooming artefacts and improved the image quality. It can be expected to improve diagnostic performance for the detection of in-stent restenosis on coronary CTA images.
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Authors: Jagat Narula; Y Chandrashekhar; Amir Ahmadi; Suhny Abbara; Daniel S Berman; Ron Blankstein; Jonathon Leipsic; David Newby; Edward D Nicol; Koen Nieman; Leslee Shaw; Todd C Villines; Michelle Williams; Harvey S Hecht Journal: J Cardiovasc Comput Tomogr Date: 2020-11-20